Quality assurance

The quality assurance process ensures that the content and format of the stored data corresponds with the description of the data, in accordance with the specified criteria.

Quality indicators include data

flawlessness

regulatory compliance

consistency

comprehensibility

unambiguity

updates

Measures forecasting the quality of data are recorded in the data management plan, which includes descriptions of data

collection methods

structure

recording

use

standards

storage

The data management plan shall be written, accepted and applied, during and after research. Particularly after research it must be ensured that the data has been properly stored and adequate data protection has been afforded to sensitive data. Peer review is also part of the quality practices.

Information on quality assurance results is recorded in the metadata.

Please also read through the quality management manual of your university or institute.